The Global Positioning System (GPS) is used across many facets of society. Individuals and private organizations can be reliant on GPS for leisure and/or to provide services to customers. Government agencies can use GPS in the course of providing general as well as emergency services. Often, the expediency and consistency of the services is subject to the integrity of the received GPS signal. The integrity of the GPS signal at the receiver is essential for ensuring the generation of Position, Navigation, and Timing data (PNT). Industrial systems, such as those involving power distribution, transportation, and communications can rely heavily on PNT data for system operation and/or maintenance.
The use of direct spread spectrum coding enables a GPS signal to be processed with receive power well below the noise floor of most receivers. This feature however makes the GPS receiver vulnerable to interference, which has the effect of degrading or preventing reception of a GPS signal. Narrowband interference (e.g., jamming or jammer signals), whether intentional or unintentional is generally in the form of a tone. The tone can be constant or time-varying, such as a pulsed tone, hopped tone, or swept tone. As a result, private and government use of GPS is vulnerable to disruption with commercially available jamming devices.
Known systems describe an approach for suppressing jamming signals using spatial nulling. The system includes a plurality of channels for receiving signals from GPS satellites. Each channel includes an antenna element, receiver, digitizer, and an adaptive notch filter. The notch filters provide outputs to one or plural spatial combiners. Temporal filters are arranged upstream of the spatial combiner so that narrowband jamming signals can be suppressed. Suppression is achieved using adaptive FIR filters that attenuate narrowband jamming signals up to 60 to 80 dB. The GPS signals within the received signals are undistorted, which allows them to be acquired and tracked by the receiver.
Another known technique is directed to the attenuation of frequency swept signals, which sweep across a given frequency band appearing to have a bandwidth that appears greater than it actually is or is pulsed on and off so that it is present during an entire block of anti-jamming processing. The signals are passed through a dyadic filter, which is composed of a plurality of wavelet transforms which allow analysis of the signal in both time and frequency domains. A covariance matrix is generated for each wavelet transformation, and is used to weight the individual elements in the respective wavelet transforms. This enables nulling undesired signal components. An inverse wavelet transform is applied to the nulled wavelet transform to reconstruct the GPS signal.
The dyadic filter decomposes the frequency space equally into low- and high-pass channels and decimates the channel by a factor of two at each stage. As a result, scaling is required at each level to stretch a cell for the low-pass channel and compress a cell for the high-pass channel. This fixed scaling can result in an increase in the number of stages required to successfully process a jammer signal, particularly a frequency agile jammer signal. Moreover, while the dyadic filter can effectively suppress frequency-shifting jamming signals, it is not optimized to process “chirp” type wavelets. The design of a dyadic wavelet transform encompasses a large number of transformers and can be further complex given that scaling, frequency resolution, and shifting cannot be defined independent of one another.
A technique for interference mitigation in a Global Navigation Satellite System (GNSS) is discussed in “Use of the Wavelet Transform for Interference Detection and Mitigation in a Global Navigation Satellite Systems”, Luciano Musumeci and Fabio Dovis, International Journal of Navigation and Observation, vol. 2014, article ID 262186, 14 pages (Hindawi Publishing Corporation, Feb. 26, 2014), the entire content of which is hereby incorporated by reference. The wavelet-based mitigation algorithm includes a decomposition phase, a detection-mitigation phase, and a reconstruction phase. In the decomposition phase, a received GNSS signal is filtered using a wavelet transform that is extended to obtain wavelet packet decomposition (WPD). The filter can include any number of stages that is determined by the spectral characteristics of the interference signal. During the mitigation phase, a blanking threshold operation is performed in each scale at the output of the filter bank to suppress the coefficients associated with interference components. In the reconstruction phase, an inverse wavelet packet transform is applied to the wavelet scales. This approach uses wavelet filter banks to obtain a complete decomposition of the received signal and provide Wavelet coefficients. The coefficients representing interference information are blanked using thresholding criteria. The reconstructed signal is free of interference. This technique, however, requires a large number of transformers to isolate the interference while providing the redundancy necessary to reconstruct the environment.
As described in “An Analytic Wavelet Transform With a Flexible Time-Frequency Covering”, by Ilker Bayram, IEEE Transactions On Signal Processing, Vol. 61, No. 5, pp. 1131-1142 (Mar. 1, 2013), the entire content of which is hereby incorporated by reference, a known analytic wavelet transform can be designed for specifying the dilation factor, Q-factor, and redundancy. These parameters are not independent of one another as the dilation factor sets an upper bound on the Q-factor, the Q-factor sets an upper bound on the shift parameter, and the redundancy parameter is a function of the dilation, Q-factor, and shifting parameters. A filter bank constructed from the transformer includes a low-pass channel and an analytic high-pass channel. The low-pass channel is iterated to reduce or decompose the frequency space at each stage. The high-pass channel is used for analysis of the signal.